Nanoparticles influence miscibility in LCST polymer blends: from fundamental perspective to current applications

Tanyaradzwa S. Muzata , Jagadeshvaran P. L. and Suryasarathi Bose *
Department of Materials Engineering, Indian Institute of Science, Bangalore 560012, India. E-mail: sbose@iisc.ac.in; Tel: +91-80-2293-3407

Received 3rd April 2020 , Accepted 14th July 2020

First published on 28th July 2020


Polymer blending is an effective method that can be used to fabricate new versatile materials with enhanced properties. The blending of two polymers can result in either a miscible or an immiscible polymer blend system. This present review provides an in-depth summary of the miscibility of LCST polymer blend systems, an area that has garnered much attention in the past few years. The initial discourse of the present review mainly focuses on process-induced changes in the miscibility of polymer blend systems, and how the preparation of polymer blends affects their final properties. This review further highlights how nanoparticles induce miscibility and describes the various methods that can be implemented to avoid nanoparticle aggregation. The concepts and different state-of-the-art experimental methods which can be used to determine miscibility in polymer blends are also highlighted. Lastly, the importance of studying miscible polymer blends is extensively explored by looking at their importance in barrier materials, EMI shielding, corrosion protection, light-emitting diodes, gas separation, and lithium battery applications. The primary goal of this review is to cover the journey from the fundamental aspects of miscible polymer blends to their applications.


image file: d0cp01814g-p1.tif

Tanyaradzwa S. Muzata

Tanyaradzwa S. Muzata is currently a PhD research scholar at the Department of Materials Engineering, Indian Institute of Science (IISc). He obtained his BTech degree in Chemical and Process Systems Engineering from Harare Institute of Technology (HIT) and a MTech degree in Polymer Technology from Delhi Technological University (DTU). Currently his research area is phase separation and structure–property correlations in LCST polymer blend systems.

image file: d0cp01814g-p2.tif

Jagadeshvaran P. L.

Jagadeshvaran P. L. is currently a graduate research scholar at the Department of Materials Engineering, Indian Institute of Science (IISc). He obtained his bachelor's degree in Plastics Technology from Central Institute of Petrochemical Engineering and Technology, Chennai, and master's degree in Materials Engineering from IISc, where he worked on phase separation in LCST polymer blends. Presently, his work is focused on the development of thin coating formulations for textiles aimed at EMI shielding applications.

image file: d0cp01814g-p3.tif

Suryasarathi Bose

Suryasarathi Bose is currently an Associate Professor at the Indian Institute of Science (IISc), Bangalore, India. He received his PhD degree from Indian Institute of Technology (IIT), Bombay. For a brief period, he worked as a research associate at IIT Bombay before he joined Prof. Paula Moldenaers's group at Katholieke University of Leuven (Belgium) as a postdoctoral researcher. His research interests include polymer blends, self-assembly of nanomaterials using phase separation in polymer blends as a tool, carbon nanotubes and graphene-based polymer nanocomposites for EMI shielding and water filtration membrane applications, rheology and structure–property correlations in homopolymers and blends.


1 Introduction

The addition of nanoparticles into polymer blends is one way of enhancing the overall properties of polymers such as optical, mechanical, flame retardancy, electrical, and thermal properties.1–3 Since miscible polymer blends can find use in some industrial applications, it is of paramount importance to understand the fundamental aspect of their miscibility in the presence of nanoparticles. Incorporation of nanoparticles in polymer blends alters the dynamics of polymer chains since polymer chain dynamics is mainly dependent upon the statistical ordering of the nanoparticles on them. Segmental dynamics of miscible polymer blends has been well reported in one of the recent reviews,4 and hence this aspect will not be covered in this review article. Incorporation of nanoparticles in miscible polymer blends alters the phase separation diagram of the two polymers. This is mainly due to the specific interactions between the nanoparticles and one of the polymers constituting the blend. Thermodynamics mainly governs the stability of miscible polymer blends. The presence of nanoparticles in the blend affects the thermodynamic interaction parameter of the two polymers. This usually results in either a decrease or an increase in the demixing temperature of the two polymers. Many researchers have mainly focused on the incorporation of nanoparticles in polymer blends but the main hindrance to achieving exciting results is the agglomeration of nanoparticles inside the host matrix. To overcome this challenge many methods have been developed such as changing the processing conditions, the use of anisotropic materials, the use of magnetic field, and grafting of organic polymer chains on the surface of inorganic nanoparticles.5,6 Grafting of polymer chains on the surface of nanoparticles through covalent bonding to avoid the polymer mediated interparticle attraction is an effective strategy.7 Polymer grafted nanoparticles are now being widely used to prevent secondary agglomeration in the host matrix. The grafted polymer chains are chemically identical to the host matrix ensuring that there are no competing enthalpic interactions. Only entropic effects are prominent which result in good dispersion characteristics. When the polymer chains of the matrix are of low molecular weight the polymer chains penetrate the grafted polymer chains to maximize their translational entropy. In the case of high molecular weight of the host matrix the translational entropy decreases and the cost of brush swelling increases resulting in the chains being expelled from the brush which leads to dewetting. Dewetting and wetting are mainly determined by the graft density. Wetting to dewetting transition occurs when there is an increase in the graft density due to an increase in the stretching cost of the grafted chains. This review highlights the effect of brush length and brush density in the following sections.

Factors governing localization of nanoparticles in polymer blends have been extensively studied. Fenouillot et al.8 wrote a well-articulated review describing the mechanism of nanoparticle migration and how the nanoparticles localize in polymer blends. In a review article by Pawar et al.,9 the different types of mechanisms governing the localization of nanoparticles in biphasic blends are highlighted. This review highlights other factors like graft density, tuning of the polymer chain length, use of Janus nanoparticles, and the π–π interaction between nanoparticles (carbon nanotubes and graphene-based nanoparticles) and the host polymers that influence their localization in the blends. This review also fills the gap pertaining to miscible polymer blends as it extensively looks upon the advantages of polymer-grafted nanoparticles and how they affect miscibility and expatiates upon the various industrial applications of miscible polymer blends in the last section.

2 Processing of polymer blends

It is very difficult to establish a single polymer blending process for miscible polymer blends because of their different phase separation temperatures. LCST polymer blends usually phase separate at high temperatures; therefore it is better to process them by solution mixing since melt mixing requires high temperatures which might be way above the phase separation temperature of polymer blend systems. In the case of polymer blends such as PMMA/PVDF melt mixing is a viable option because their interaction is so strong that their miscibility is not affected by high-temperature processing conditions.10 Understanding the preparation of polymer blends is of paramount importance because the method of preparation can affect the overall properties of the resultant polymer blends.11–14 Miscibility of polymer blends can be influenced by the method of polymer blend preparation, and the method of blend preparation can result in immiscible, partially miscible, and miscible polymer blends.15 In their work Etxeberria et al.16 showed that the solvent casting method produced a phase-separated polymer blend system and the precipitation method resulted in a polymer blend with improved homogeneity. Therefore, it is of paramount importance to study the sample preparation. The dispersion of nanoparticles is also influenced by the method of mixing. Ke et al.17 in their work postulated that the dispersion of MWCNT in PVDF was influenced by the method of preparation; at low concentration below 5 wt% of MWCNT the dispersion was found to be better in samples prepared by solution mixing than in samples prepared by melt mixing. At higher concentration melt mixed samples showed better dispersion than solution mixed samples. The methods which are used to prepare polymer blends are many, but this review will only focus on the commonly used methods such as solution and melt mixing.

2.1 Solution mixing

Solution mixing involves the mixing of two polymers in a common solvent with the use of a magnetic stirrer or shear mixer under specific conditions. Different types of solvents can be used for dissolving the polymers depending on their solubility parameter. After the polymers are mixed, the solvent is allowed to dry at room temperature for 24 h followed by drying in a vacuum oven until the solvent has completely evaporated from the polymer blend. The vacuum is applied slowly to prevent the formation of gas bubbles. This method is best suited for polymers that dissolve in a common solvent and for those having low viscosities. Polymer blend systems can be miscible but once they are dissolved in a solvent, they can phase separate mainly because the solvent may favorably interact with one of the polymers. The main advantage of solution mixing is that thermal degradation of polymers is minimized in comparison to melt mixing, it allows good dispersion of nanoparticles and it consumes less energy. Polymer composites prepared by solution mixing have been shown to have better nanoparticle dispersion compared to those prepared by melt mixing at lower filler loading. Sui et al.18 studied the dispersion of CNTs in thermoplastic polyurethane which was processed by both solution mixing and melt mixing methods. They observed that the solution mixing method resulted in good dispersion when the filler loading was less than 2.5 wt%. Melt mixing proved to be a better method for dispersing the nanoparticles at higher filler loading. Although solution mixing might seem to be a viable mixing method, it possesses a great number of limitations. This method is not industrially viable because it requires the use of large volumes of highly volatile solvents which are detrimental to both the environment and the health of human beings, and these solvents should be handled with great care because some of them are highly flammable. In some cases not all of the solvent is removed during evaporation, and traces of solvents can have detrimental effects especially on polymers used as scaffolds.19 Lately, researchers have been exploring solvent-free methods to minimize the use of solvents in carrying out reactions.20

2.2 Melt mixing

Melt mixing is a common method that is used to mix polymers in their melt state by applying heat and subjecting the polymer melt to intense shear using rotating screws. This method is suitable for polymers which have high viscosities and which do not easily dissolve in common solvents at room temperature. Counter (rotating in the opposite direction) or co-rotating (rotating in the same direction) screws can be used in melt mixers. The screws are designed to be intermeshing whereby the flights of the first screw will easily move in the channels of the second screw. Shah et al.21 showed that the degree of mixing is very high in co-rotating screws in comparison to counter-rotating screws. They further explained about the high-pressure build up in counter-rotating screws. In melt mixing the order in which the polymers and nanoparticles are added is of great importance because it can alter the properties of the polymer blend system. The most frequently used mixing protocol is when both components are added together into the melt mixer; the high temperature will result in the polymer being viscous hence allowing migration of the nanoparticles in one of the phases. Usually, the nanoparticle migration might not be governed by thermodynamics, but migration might be based on which polymer melts first. Melt mixing is one of the most favored types of methods to blend two polymers because it does not pose any environmental threats and it is a less time-consuming process in comparison to solution mixing. The main limitation of melt mixing miscible polymer blends is that the processing temperature might be way above the miscibility temperature of the polymer blends resulting in a phase-separated system. Usually, crystalline polymers are processed at temperature 50 °C above their melting point and amorphous polymers at 100 °C above their glass transition temperature; these temperatures might be above the miscibility temperature range of the polymer blend. Many parameters can be varied in melt mixing; in their work Chaudhuri et al.22 were able to study the effects of melt mixing processing conditions of ultra-high molecular weight polyethylene and high-density polyethylene. They varied the many processing parameters such as the time of blending and the screw speed and observed that a high screw speed leads to a better dissolution of UHMWPE into HDPE.

3 Mechanisms of phase separation

Phase separation in polymer blends usually occurs via spinodal decomposition and nucleation and growth. The occurrence of spontaneous concentration fluctuations usually leads to the former while the latter is a result of phase separation occurring via the metastable region. Nucleation theory stipulates that minute droplets of the minor phase evolve after a certain period in the homogeneous mixture which would have been brought via the metastable region. Droplet growth is usually facilitated by diffusion of the polymer from the supersaturated continuum, and the droplet further grows in its size due to droplet coalescence or by Ostwald ripening where the larger droplets increase in size at the expense of the smaller droplets.

Spinodal decomposition is usually due to polymers phase separating spontaneously. Usually, homogeneous mixtures in the metastable state must vanquish the free energy barrier to nucleate another phase. Spinodal decomposition results in a bi-continuous two-phase structured system. The size of the spinodal structures formed first is mainly governed by quench depth. After the formation of a bi-continuous structure, interfacial tension causes the structures to be reduced in their surface area through a domain size increase of the phase-separated system. Tanaka23 observed another special type of phase separation mechanism known as the viscoelastic phase separation in a dynamic asymmetrical system of PS/PVME. Dynamic asymmetrical systems are polymer systems that have different dynamics in their melt state due to a large difference in their glass transition temperatures. In viscoelastic phase separation, the stresses which are self-generated in the more elastic phase mount up resulting in a percolated network structure in the phase showing more elasticity. After some time, the percolated structure coarsens mainly due to shrinkage in volume resulting in disconnected domains and phase inversion.

4 Factors governing the miscibility of polymer blends

An in-depth analysis of how thermodynamics affects the miscibility of polymer blends is of paramount importance in an endeavor to understand the effects of nanoparticles on miscibility. The thermodynamics which governs the miscibility of amorphous polymer blends can be regarded as the same as the one which governs liquids. The formation of a miscible polymer system in blends is mainly associated with the Gibbs free energy which can be represented as follows:
ΔGmix = ΔHmTΔSm
where ΔGmix is the Gibbs free energy of mixing, ΔHm and ΔSm are the enthalpy and entropy of mixing respectively and T is the temperature. Polymer chains have a low entropy of mixing due to their high molecular weight, hence entropy does not play a major role in enhancing miscibility as compared to enthalpic effects. Polymers that form interactions such as hydrogen–hydrogen, ionic and dipole–dipole interactions between each other are more favorable to be homogeneous because of the enthalpic effects which cause the Gibbs free energy to be negative.24 Flory and Huggins came up with a classical theory to explain the miscibility of two polymers. The Flory–Huggins theory was an add-on of the solution theory which only governed small molecules. Due to large polymer chain length, the regular theory will not suffice for polymers, henceforth homogeneity of polymer blends cannot be achieved at a segmental level. Usually, there is a certain level of heterogeneity which is analogous with thermodynamic miscible systems. This has resulted in such blends to be regarded as partially but not fully miscible.

Enthalpic effects in polymer blends without nanoparticles play a major role in enhancing miscibility but in miscible polymer blends containing nanoparticles, entropic effects are dominant between the nanoparticles and the polymer chains. Miscibility between nanoparticles and polymers usually occurs when the chains are bigger than the nanoparticles; in this case, miscibility is mainly governed by entropic factors. To avoid aggregation particle–particle attraction must be avoided and particle–polymer attraction must be enhanced. Enthalpic factors are used to control miscibility for example between PEO and silica nanoparticles where hydrogen bonding is dominant. The strength of interaction governing the miscibility of polymer blend systems is mainly governed by the composition of the polymer blend system and the chemical structure of the polymers involved.25 Polymer blend systems such as PMMA/PVDF have strong interactions due to the existence of two intermolecular interactions which are hydrogen bonding between the –CH2 of PVDF and the carbonyl group of PMMA and the dipole–dipole interactions between –CF2 of PVDF and –CH2 of PMMA.26 In some polymer blend systems, miscibility occurs in unique ways. The miscibility of PMMA/SAN has been reported to occur through a special type of interaction known as the copolymer repulsion effect. As mentioned above, entropy and exothermic heat of mixing are the main factors that determine miscibility, but in large macromolecular structures, entropy runs low, hence is considered to be negligible. This results in exothermic enthalpy of mixing to be the main determining factor governing miscibility in polymer blends. The exothermic enthalpy of mixing in PMMA/SAN has been reported to arise from the interchain repulsion which occurs in SAN between its comonomer units. PMMA has been reported not to form miscible polymer blend systems with both PS27 and PAN28 further supporting the existence of the copolymer repulsion effect. This has been further explained by Keskkula et al.,29 who studied more about the interaction between homopolymers and copolymers resulting in miscible polymer blends. However, there is another school of thought which argues that the copolymer repulsion effect is not the one responsible for miscibility in PMMA/SAN. Feng et al.25 postulated that the copolymer repulsion concept is oversimplified and lacks direct experimental backing. They reported that the miscibility of PMMA/SAN is because of intermolecular interactions that occur between the PMMA carbonyl group and the phenyl ring present in SAN backing their argument with NMR experimental studies. However, the take-home point between the two schools of thought is that enthalpy is a major factor in determining miscibility. The miscibility of PMMA/SAN is mainly governed by the acrylonitrile content in SAN. The AN content in SAN should be in the range of 6.3–32.8 wt% for miscibility to occur. Fowler et al.30 reported that the highest phase separation temperature is obtained when the AN content in SAN ranges from 10 to 14 wt%.

5 How nanoparticles influence the phase separation of miscible polymer blends

It has been well reported that the addition of nanoparticles in miscible polymer blends usually increases the temperature at which they phase separate.31–33 The incorporation of nanoparticles results in a change of the phase separation diagram and the kinetics of phase separation, and alters the interaction parameter between two polymers. The addition of nanoparticles in a polymer blend system results in one of the polymers selectively adsorbing on the surface of the nanoparticles. This leads to the formation of a border layer on the nanoparticle surface resulting in a change in the composition of the bulk system. The incorporation of nanoparticles decreases the interaction parameter leading to miscibility due to selective adsorption effects of one polymer on the nanoparticle surface. Xavier et al.31 reported that incorporating 0.25 and 0.5 wt% of multi-walled carbon nanotubes in PS/PVME polymer blends delayed phase separation. By introducing silica, Huang et al.34 were able to see an increase in the phase separation and also a decrease in the interaction parameter in PMMA/SAN. The authors attributed both the delay in demixing and the decrease in the interaction parameter to the favorable interaction of PMMA chains on the surface of silica. It has been postulated that irrespective of their localization in the two polymers, nanoparticles increase the phase separation of polymer blends. In their work Kou et al.35 incorporated graphene nanoplatelets in a PMMA/SAN miscible polymer blend system and they were able to successfully prevent domain coarsening. Ginzburg36 went a step further by taking into consideration the effect of particle size and geometry and coming up with a theory that postulated how spherical nanoparticles affect the demixing temperature of polymer blends. According to his theory, nanoparticles can either increase or decrease the demixing temperature depending upon the radius of the particle and the degree of polymerization. When the radius of the particle is less than the radius of gyration of the polymer, incorporation of nanoparticles enhances miscibility due to a decrease in enthalpy of mixing. This is mainly because of more polymer–particle interactions and less polymer–polymer interactions. The radius of the nanoparticles in spherical nanoparticles is a major determining factor in facilitating miscibility of polymer blends.

5.1 Polymer grafted nanoparticles

Miscibility of polymer blends has been well reported to be improved when polymer grafted nanoparticles are used in comparison to bare nanoparticles.37,38 Polymer grafted nanoparticles are nanoparticles that have polymer chains covalently tethered upon their surface.39 Polymer grafted nanoparticles can be prepared by grafting to and grafting from methods as shown in Fig. 1. The polymer grafted nanoparticles have been extensively used in other applications such as drug delivery, designing of water membranes,40 organic field-effect transistors,41 photovoltaics,42 and theranostic application.43 Polymer grafted nanoparticles have been reported to increase both the binodal and the spinodal phase separation temperature of polymer blend systems. Kar et al.37 were able to functionalize MWCNT with polystyrene polymer chains by nitrene chemistry. When they incorporated the grafted nanoparticles in the PS/PVME polymer blend, they were able to observe a significant increase in the demixing temperature in comparison to neat nanoparticles. They explained this significant increase in the demixing temperature by statistical mechanics. The PS-g-MWCNT nanoparticles were found to be localized in the PVME phase, and this resulted in favorable interactions between the grafted PS chains and the PVME matrix chains since PVME acted as a good solvent. This led to a loss in entropy (which is more in polymer grafted nanoparticles compared to bare nanoparticles) due to polymer swelling. An increase in enthalpy is encountered due to the favorable interaction of PS-PVME chains leading to enhanced thermodynamic miscibility. Incorporation of polymer grafted nanoparticles increases the field of application of polymer composites. Bare nanoparticles have been reported to increase the mechanical properties of polymers but in some cases, they decrease the mechanical properties due to immiscibility between them and the host polymer matrix hence leading to agglomeration.
image file: d0cp01814g-f1.tif
Fig. 1 Mechanism of developing polymer grafted nanoparticles. (Reproduced from ref. 44 with permission from ACS, copyright 2017.)

The main advantage of polymer grafted nanoparticles is that they act as steric stabilizers hence preventing agglomeration of nanoparticles. Through simulation Hao et al.45 have recently postulated that polymer grafted nanoparticles also increase the crystallinity of polymers. The presence of polymer chains tethered on the surface of the nanoparticles also affects the dynamics and structure of the nanoparticles.46 Polymer grafted nanoparticles are one of the effective ways for improving the spatial distribution of nanoparticles in the host matrix. Even though grafted polymer chains are similar to the host polymer chains, the prevention of agglomerates is not always guaranteed. Low polymer graft density can result in phase separation between the grafted chains and the host matrix, a phenomenon known as allophobic dewetting.47,48 This phenomenon can also be observed when the matrix polymer chains have a higher molecular weight in comparison to the tethered polymer chains. Increasing the graft density will result in wetting of the tethered and the host matrix. It should be highlighted that graft density is not the only single factor in determining dispersion, but the radius of the particle, chain-end mobility, and the polydispersity of the grafted chains are also some of the factors which can affect dispersion. Kumar et al.49 wrote an excellent review article on the spatial distribution of polymer grafted nanoparticles and the properties of the composites containing polymer grafted nanoparticles.

6 Methods of determining phase separation of miscible polymer blends

There are a multiplicity of methods which can be used to determine the phase separation or demixing temperature of miscible polymer blends.50,51 Rheology has been widely used in determining the demixing temperature due to its ability to produce various rheological fingerprints.31,52,53 It can correlate the microstructure to the viscoelastic properties of the polymer blends. The rheological analysis is one of the most favorable methods for analyzing the phase behavior of miscible polymer blends, both dynamically asymmetrical and weakly asymmetrical, because it is not affected by the presence of nanoparticles.31,54,55 Measurements done by rheology are quick to detect polymer chain reputation, interfacial tension, and diffusion in polymer blends, hence can be used to observe phase separation at early stages.50 Rheology is also used to determine the localization of nanoparticles,56 study the phase separation kinetics,53 thermodynamics involving phase separation, and also to probe the type of morphology of the demixed polymer blends.57 Jafar et al.54 in their work were able to probe the phase separation mechanism in PS/PVME. They used melt rheology to distinguish between spinodal decomposition, nucleation and growth and viscoelastic phase separation in the PS/PVME polymer blend system. Sharma et al.58 also studied the miscibility of deuterated polystyrene (PSD) and PVME by rheology. They were able to determine the miscibility range of their blend system. Determination of phase separation by rheology has been proven to be an effective method than light scattering and optical techniques because it is not affected by the presence of nanoparticles and it has high resolution which is mainly dependent upon the oscillatory frequency. Other methods used to determine the miscibility of polymer blend systems are also highlighted in the following sections.

6.1 Rheology

Isochronal temperature ramps. One of the most frequently used rheological fingerprints in determining the demixing temperature of miscible blend systems is temperature sweeps.59,60 In isochronal temperature ramps, the percentage strain rate and frequency applied in this rheological fingerprint are kept constant whilst varying the temperature. When the temperature increases the polymer chains start to become mobile due to Brownian motion resulting in a decrease in the elastic part of the polymer which is the storage modulus (G′). This is mainly observed in dynamic asymmetrical polymer blends like PS/PVME. When nearing the phase separation region, there is an interchange that is rather a bit complex due to the concentration fluctuations and movement of the polymer chains which induces more stress into the system as elaborated by Kapnistos et al.61 The deviation from the linearity of the storage modulus in dynamic symmetrical polymer blends is taken as the demixing temperature.62 In dynamic asymmetrical polymer blends, there is an increase in the storage modulus with temperature, which is due to concentration fluctuations and domain interfaces, which induces extra stress. At the phase separation temperature thermodynamics takes over and in weakly dynamic asymmetric polymer blends51,60,63 a small deviation from linearity is observed but in strongly dynamic asymmetrical blends, a large deviation from linearity is observed. In conclusion, it is quite easy to determine the demixing temperature of strongly dynamic asymmetrical blends using isochronal temperature ramps as seen in Fig. 2.
image file: d0cp01814g-f2.tif
Fig. 2 (a) Determination of the phase separation temperature by isochronal temperature ramps. (b) Determination of the binodal phase separation temperature of neat PS/PVME. (c) Determination of the binodal phase separation temperature with 1 wt% of sNP. (Reproduced from ref. 64 with permission from RSC, copyright 2014.)
Isothermal frequency sweeps. Isothermal frequency sweeps are one of the widely used rheological fingerprints to determine the demixing temperature of miscible polymer blends. In isothermal frequency sweeps, the storage modulus is varied as a function of frequency whilst applying a constant strain that will be lying in the linear viscoelastic region at a specific constant temperature. Usually, the storage modulus is the one that is used rather than the loss modulus because the change in G′ is more evident in comparison to G′′ when phase separation occurs.65 In miscible polymer blends, the probing of the demixing temperature is usually observed at lower frequencies when G′ deviates from the scaling law (G∼ ω2). The shoulder which is observed at low frequencies is mainly attributed to the relaxation of the new domains created as a result of phase separation.52,66,67 In homopolymers, there is no deviation from the scaling law, hence they can be used as a reference in comparing with miscible polymer blends at temperatures above the demixing temperatures. Therefore a homogeneous polymer blend will have the same viscoelastic properties as that of a homopolymer but differs only when it goes into the heterogeneous phase. Isochronal frequency sweeps are not only used to determine the miscibility of polymer blends, but they can also be used to probe the type of morphology when the polymer blends phase separate. In off-critical compositions, a shoulder manifests in the low-frequency regime, and the increase in the elastic properties is due to the droplet-matrix morphology. In co-continuous morphology, the storage modulus at low frequencies shows a power law behavior.
Cole–Cole plot. Cole–Cole plots have been recommended to be very sensitive in probing the demixing temperature of miscible blends.65 These plots reveal the relaxation of polymer blends; at high frequencies the plot shows viscoelastic relaxation and at low frequencies, the relaxation is a result of domain deformation. The plots are usually obtained at different temperatures by plotting the imaginary (η′′) viscosity component as a function of the real part of viscosity (η′). For miscible polymer blends, the plot shows a semi-circular arc and when the polymer blend system is phase-separated the plot shows a semi-circular arc with a drifting tail. This extra tail is because of the additional relaxation due to phase-separated domains. For weakly dynamic asymmetrical blends, Cole–Cole plots are the most sensitive rheological fingerprints in comparison to isochronal temperature ramps and TTS (Time Temperature Superposition). These plots have been widely used by researchers to determine miscibility in polymer blends mainly because of their simplicity and accuracy. Huang et al.34 were able to study the effect of silica nanoparticles through the use of Cole–Cole plots when they incorporated them in PMMA/SAN. In their work, Li et al.66 also used Cole–Cole plots in investigating the effects of multiwalled carbon nanotubes on the miscibility of PMMA/SAN.
Hans plot. The miscibility of polymer blends can also be determined by the Hans plot,68,69 where the effect of temperature and frequency is eliminated. It has been widely reported that for a polymer to be considered miscible the plot of G′ as a function of G′′ should be linear. Non-miscibility of a polymer blend is observed when there is a deviation from the linear relationship.

6.2 Determination of miscibility by DSC

DSC is one of the most widely used tools to probe the interaction between two polymers in a polymer blend. The glass transition temperature (Tg) obtained from DSC is often used as a measure to check the extent of miscibility in a polymer blend. Glass transition in a polymer is a characteristic transition of its amorphous phase. At Tg, the polymer transforms into a rubbery state from a glassy state which is supposedly attributed to the enhanced segmental mobility. Tg for a polymer, in general, would elucidate its mechanical behavior at room temperature and also its thermal behavior. It should also be highlighted that there is a sharp change observed in the modulus of the polymer once glass transition kicks in ref. 70.

Polymer blends are classified into miscible (single-phase) and immiscible blends (phase-separated) based on the nature of interactions between segments of individual polymers. A single glass transition was once a widely used criterion to predict miscibility in a polymer blend.71–76 Miscible blends are known to exhibit a single Tg, a value intermediate between the Tg's of the individual polymers. When the blends are immiscible, they show two distinct Tg's corresponding to the glass transitions of the individual polymers.

Crispim et al.77 employed DSC as a tool to determine the effect of the solvent used on the miscibility of poly(methyl methacrylate) (PMMA)/poly(vinyl acetate) (PVAc) blends. Different solvents like chloroform, toluene, and N,N-dimethyl formamide (DMF) were used to prepare the blends at different temperatures. It was observed that in this system, the miscibility of the two polymers depended upon the type of solvent and temperature. The glass transition from DSC was used to prove this phenomenon; whenever the blend turned immiscible there were two glass transitions seen in the DSC thermogram. The composition considered under study in this work was 50/50 which exhibited a LCST close to 125 °C (Fig. 3(a)). The films were cast at two different temperatures, viz. 30 °C and 50 °C. Samples prepared from chloroform and toluene at 30 °C were transparent indicating miscibility while those prepared from DMF were opaque indicating their immiscible nature. This was attributed to the lack of specific interactions with DMF which makes the blend immiscible at both the temperatures of fabrication. In toluene, the presence of specific interactions makes the blends attain smaller domain sizes (which is an indication of a higher level of miscibility). The phase miscibility of chloroform which is a good solvent for both PMMA and PVAc is accounted based on conformational energy. When a solvent is evaporated, the chain mobility gets frozen thereby resulting in a conformation of high energy. But with chloroform, interactions like hydrogen bonding with the solvent by the polymeric species would provide sufficient energy to overcome the conformational energy barrier thereby resulting in miscibility. It must be noted that PVAc undergoes a glass transition at 40 °C. Hence at temperatures above 40 °C, macromolecules of PVAc start diffusing to PVAc-rich regions from the interphase thereby resulting in phase segregation. This is hence responsible for the opacity of samples prepared at 50 °C and also for the two Tg's in the DSC of such samples. This makes the fact clear that, when polymeric blends are prepared by solution mixing, interactions with the solvent has a dominant effect on the miscibility of the blend.77


image file: d0cp01814g-f3.tif
Fig. 3 (a) Cloud point curve for the PMMA/PVAc system. DSC curves for (b) neat PMMA and neat PVAc cast from toluene at 30 °C obtained after pre-heating to 110 °C, (c) 50/50 PMMA/PVAc films cast from chloroform at 30 °C obtained after pre-heating to 110 °C (curve A) and 180 °C (curve B), and (d) 50/50 PMMA/PVAc films cast from toluene at 30 °C (curve A) and 50 °C (curve B) both obtained after pre-heating to 110 °C. (Reproduced from ref. 77 with permission from Elsevier, copyright 1999.)

Fried et al.78 had used differential scanning calorimetry to assess the compatibility in the blends of poly(2,6-dimethyl-1,4-phenylene oxide) (PPO) and random copolymers of styrene and 4-chlorostyrene. In such a case, compatibility was assessed by the appearance of a single glass transition temperature in DSC whose value is in between those of the unblended copolymers and PPO. Interestingly, as the content of 4-chlorostyrene increased above 67.8 mol%, the blend began to phase separate which manifested as two distinct Tg's (as seen in Fig. 3). Further, the width of the glass transition was used as a measure to characterize the compatibility between PPO and the copolymers. The compatible blends (PS, B, and C) had a wide glass transition which tends to increase with an increase in the content of 4-chlorostyrene as shown in Fig. 4. It was observed that the width reaches a maximum at 67.1% and then decreases once the blends begin to phase-separate. This behavior was attributed to the phase homogeneity in the sample. The broad glass transition that is seen in the miscible blends is a continuous distribution of glass transitions that broaden out as a single transition. The molecules of a local region associated with a transition relax to an equilibrium enthalpy state from a lower enthalpy state with no barrier, after the completion of every small transition corresponding to the distribution. Because of such enthalpic relaxations over a large range of temperatures, there is no excess enthalpy at the end of the transition. A broad glass transition also reveals the fact that the constituent phases contain some amount of the other component. For instance, when a blend A/B phase-separates, it forms two phases, viz. a phase rich in A and a phase rich in B. But when the blends phase-separate, the transitions become narrow and the excess enthalpies characteristic of the pure components reappear owing to the absence of relaxations.78


image file: d0cp01814g-f4.tif
Fig. 4 DSC thermograms of the different blends which become immiscible with an increase in the concentration of 4-chlorostyrene. (Reproduced from ref. 78 with permission from ACS, copyright 1978.)

In an attempt to study the phase behavior of semi-crystalline blends with rubber, poly(trimethylene terephthalate) (PTT)/EDPM, Ravikumar et al.79 used calorimetric studies which gave some notable insights. PTT being a semi-crystalline polymer has its Tg at 50 °C while EPDM has its Tg at −55 °C. The near-critical compositions showed two distinct Tg's which are an implication of phase-separated segments consisting of PTT and EPDM (Fig. 5a). However, the off-critical compositions showed a single Tg characteristic of the major phase of the polymer present. This depicted that the minor phase present is in small quantities and is hence not detected by DSC, which may also be due to the good dispersion of the minor phase. Also, the possibility of phase miscibility based on single Tg was ruled out in this case, as there is no shifting of Tg's towards each other. Since one of the components is a semi-crystalline polymer, the melting temperature Tm can also give us information about the miscibility. In a two-component polymer blend, a depression in the melting point of the semi-crystalline component implies a favorable interaction between the two polymers constituting the blend that causes a reduction in the crystallite size (Fig. 5b). This can also be considered as a basis for commenting about the miscibility of a polymer blend where one of the polymers is semi-crystalline and exhibits a prominent Tm.79


image file: d0cp01814g-f5.tif
Fig. 5 DSC scans of the different blends of PTT/EPDM showing (a) glass transition and (b) melting points. P represents the percent of PTT and E represents the percent of EPDM. (Reproduced from ref. 79 with permission from Elsevier, copyright 2005.)

6.3 Dielectric relaxation spectroscopy (DRS)

As seen above, the glass transition temperature is one of the important criteria used to assess the extent of miscibility in polymer blends. DRS is one of the characterization tools used to measure the glass transition temperature of a given polymer.

A miscible blend exhibits a single glass transition temperature which is composition-dependent and lies between that of the constituent homopolymers. The use of bulk characterization tools like DSC and DMTA to measure the Tg of a blend is considered to have a few limitations. A difference of 50 °C in the Tg's of the constituent polymers is required in DSC for the resolution of the blend phases. Also, a minimum of 10–20% of a minor phase is required for signals to be detected from it.80,81 DMTA proves to be a more sensitive tool than DSC wherein the least detectable domain is of the order of a hundred angstroms.81,82 This reveals an interesting insight about miscibility in a polymer blend that the miscibility assessed by any characterization tool is dictated by the level of sensitivity of the tool, i.e. its ability to probe heterogeneity down to different length scales.83 DRS is one of the techniques that are sensitive to heterogeneity at length scales comparable to those of molecular chains (segmental motion) thereby being sensitive to micro-heterogeneity.

DRS studies the measure of interaction of the dipole moments in a given sample with the electromagnetic field. In the context of polymers, it is their chemical structure and polarity which control the dielectric response. Along with these, conformation, the ability of interaction with molecules, and packing are some other factors which must be considered as these dictate the dielectric response of polymers. The dielectric response changes significantly at transitions like the glass transition and the sub-Tg transitions which involve local molecular motion and are observed as maxima in the dielectric loss.

Relaxation of polymer chains is characterized by a broad relaxation spectrum that spreads over a large range of length and time scales. This relaxation that is characteristic of any homopolymer will be significantly affected when it is blended with other polymers. It is well known that polymer chains in a miscible blend need not necessarily share similar local segmental dynamics and also the distribution of relaxation times for such segments is broad in comparison to that of the pure components. In a few cases, the α-relaxations show a bimodal distribution though the blends are said to be in a single phase.84,85 Consequently, this does not necessarily mean that the appearance of two such α-relaxations is a criterion for phase separation in a miscible blend. Such different relaxation times that are observed in the α-relaxations of a binary miscible blend are being accounted qualitatively based on the “dynamic heterogeneity” that comes up from the inherent difference in the segmental dynamics and as a consequence of local concentration fluctuations.86

A considerable contribution towards the segmental dynamics of polymer blends as captured by DRS is available in the literature. A basic requirement of this technique is that the polymer must be dielectrically active, which would turn out to be advantageous when one of the polymers of the blend is active dielectrically – thereby enabling the study of its segmental dynamics independent of the other components. In binary mixtures like polymer blends, it is often noticed that the local concentration fluctuates about an average value which is responsible for the broadening of α-relaxations (and thus the glass transition).24,52,87

Numerous models have been put forth to explain and simulate the distribution of relaxation times in polymer blends.88,89 The Fischer and Zetsche model90 portrays the local fluctuations in concentration as a Gaussian distribution about the average concentration and its implications on segmental relaxations about that environment. As the concentration would not be uniform, there would be a certain area rich in one component which will dominate the relaxation of segments in that region instigating dynamic heterogeneity. Jonas et al.91 developed a model that uses a Flory–Huggins type lattice to study the effect of nearest neighbor contacts on the local segmental dynamics. The coupling model92–95 attributes the relaxation behavior to cooperative motion (intermolecular and intramolecular) between polymer segments which is quantified by a coupling parameter. Thus, in polymer blends, different polymer components will have different intermolecular coupling despite being in the same environment. Further, the change in average concentration would give rise to a distribution of local environments due to concentration fluctuations being responsible for a wide range of relaxation times seen in polymer blends.

Campbell et al.96 studied the relaxation in polycarbonate/polyester blends with the help of DRS. The polyester used here was Kodar which is a copolyester of 1,4-cyclohexanedimethanol, terephthalic acid, and isophthalic acid. They were able to prove the concept of dynamic heterogeneity in the studied system even after the existence of a single Tg as characterized by different methods (as shown in Fig. 6).


image file: d0cp01814g-f6.tif
Fig. 6 T g for PC/Kodar blends as determined by different techniques. (Reproduced from ref. 96 with permission from Elsevier, copyright 2001.)

It was observed that the Tg values of the blends fall very close to the additive line of the component polymer values which indicates the existence of weak favorable interactions between the polymers. The Tg values observed by different techniques vary (those observed by DRS being the highest and those observed by DSC being the lowest) which is because of the difference in the frequency of measurement or the effective frequency and the nature of relaxations of the polymer chains probed (thermal in DSC, mechanical in DMTA and dipolar in DRS) in each technique.

Fig. 7 shows the dielectric loss spectra for polycarbonate (a) and the 40% Kodar blend (b). Each curve represents an isothermal frequency sweep where the dielectric loss is fitted to the Havriliak–Negami equation,97

image file: d0cp01814g-t1.tif
where Δε is the dielectric relaxation strength, τHN is the relaxation time, βHN is the broadness of the spectrum and γHN is the skewness of the curve. The values of βHN and γHN are unity when the relaxation is of the Debye type. When they approach zero, the curve would become broad and skewed towards high frequencies.


image file: d0cp01814g-f7.tif
Fig. 7 (a) Isothermal dielectric loss scans of the α-relaxation in 100% polycarbonate at different temperatures: (■) 158 °C, (●) 161 °C, (▲) 164 °C, (♦) 167 °C, (□) 170 °C, (○) 173 °C. (b) Isothermal dielectric loss scans of the α-relaxation in 40% Kodar at different temperatures: (●) 140 °C, (▲) 143 °C, (♦) 146 °C, (□) 150 °C, (○) 153 °C, (Δ) 156 °C and (◊) 159 °C. Curve fits of the HN equation are also shown. (---) (Reproduced from ref. 96 with permission from Elsevier, 2001.)

It is evident from the curves that with a rise in temperature the maxima of the curve shift towards high frequencies indicating an increase in the chain mobility and an increase in the dielectric loss at low frequencies which may be attributed to conductivity. They showed that the peak broadens with an increase in temperature which must be due to an increase in concentration fluctuations about the average. Further, the relaxation times as predicted by different models (Fig. 8) increase on blending which is associated with the experimental temperature being less than the Tg of polycarbonate (rigid major phase) which results in large concentration fluctuations. Now, this hypothesis can be held valid if there is a microheterogeneity that already exists in this blend which permits the relaxation of PC to dominate the relaxation behavior of the entire blend contrary to what is expect in a homogeneous blend (i.e. without microheterogeneity). Hence, even after the existence of single Tg as shown by different techniques as a measure of macroscopic miscibility there are still regions that are rich in the individual polymer components that exist.


image file: d0cp01814g-f8.tif
Fig. 8 Average relaxation time as predicted by the (a) HN model and (b) KWW model at reduced temperature (Tgd/T = 0.98) as a function of the blend composition. An additive line is given for comparison. (Reproduced from ref. 96 with permission from Elsevier, copyright 2001.)

Xavier et al.31 studied the microscopic heterogeneity in a classical system of PS/PVME that is reported to be miscible in macroscopic length scales. In this system, PVME is the one dielectrically active component which makes the study of dielectric relaxations interesting in this system. PVME has a higher dipole moment than PS indicating its ability to respond quickly to an ac field in comparison with PS. The relaxations of PVME as shown in the dielectric loss spectra (Fig. 9a) reveal the fact that the loss maxima show a strong dependence on temperature above the Tg which corresponds to α-relaxations. The PS/PVME system constitutes a blend with strong dynamic asymmetry where a lot of insights can be obtained by studying the segmental dynamics near demixing. The broadness of the relaxation spectra increases on blending but shifts towards low frequencies contrary to that observed in the previous system (PC/Kodar). This is ascribed to the retardation of the relaxations of PVME chains due to the presence of a stiffer high Tg PS component. Concentration fluctuations, that are held responsible for the broadening of the relaxations in blends, are active at temperatures well above the glass transition. Yet another interesting fact reported was that the relaxations in PVME were observable at temperatures lower than the calorimetric glass transition of the blend. This reveals the fact that though the blend is miscible its constituting polymers do not share the same segmental dynamics; PVME chains relax quickly in a frozen PS domain. This inherently indicates that the local environment around PVME is richer in PVME than the global composition though the blend is miscible on a large scale.


image file: d0cp01814g-f9.tif
Fig. 9 Dielectric loss spectra at various temperatures for (a) PVME and (b) PS/PVME 60/40 blends. (Reproduced from ref. 31 with permission from ACS, copyright 2013.)

6.4 Dynamic mechanical thermal analysis

DMTA is one of the different techniques used to determine the phases present in a given polymer blend. Every characterization technique suffers an inherent disadvantage in terms of length scales up to which miscibility can be probed. This implies that the phase composition as predicted by any technique may not always be an indicator of thermodynamic immiscibility.

Typically, a polymer blend is said to be miscible if DSC detects only a single glass transition temperature. However, DSC is not sensitive to detect miscibility down to length scales comparable to those of polymer segments where it fails to assess the phase behavior. DSC is reported to detect domains of size greater than 100 Å and is thus more of an indication of miscibility in the bulk rather than molecular length scales.

DMTA also uses the glass transition temperature (the peak in the tan[thin space (1/6-em)]δ vs. T curve) as a diagnostic tool for examining the miscibility where Tg is measured along with rheological properties like modulus and damping (as shown in Fig. 10). An advantage of measuring the glass transition by DMTA is its sensitivity and its ability to detect other sub Tg transitions that occur at low temperatures.


image file: d0cp01814g-f10.tif
Fig. 10 Basic dynamic mechanical behavior of a compatible blend (a and b) versus an incompatible blend (c and d) and pure components. (a and c) Loss tangent versus temperature. (b and d) Resilience versus temperature. (Reproduced from ref. 98 with permission from Elsevier, 1988.)

Li et al.99 investigated the phase behavior of poly(methyl methacrylate)/poly(4-vinyl phenol) (PMMA/PVPh) blends using both DSC and DMTA. All the prepared compositions showed a single glass transition as characterized by DSC indicating thermodynamic miscibility at length scales that DSC can delve into. In contrast, these blends were immiscible when investigated by NMR. The study executed gave critical discernments about the intrinsic limitations of DSC when it comes to the context of polymer blends. Fig. 11(a) shows a typical behavior of the elastic storage modulus with temperature wherein E′ changes very little in the plateau region and then decreases further indicating the occurrence of the glass transition. Another interesting point is that the plateau region extends to higher temperatures for the blends. This can be attributed to the formation of intermolecular hydrogen bonds between PMMA and PVPh which act as a physical crosslink affecting the segmental motion. The plot of log[thin space (1/6-em)]E′′ vs. T [Fig. 11(b) and (c)] for the blends shows two different relaxations corresponding to two different transitions – the first relaxation is the α-relaxation which corresponds to the glass transition and the second one occurring at high temperatures corresponds to the presence of a second phase. It can also be noticed that such relaxation at higher temperatures is not present in the case of neat PMMA. This is also evident from the graphs of tan[thin space (1/6-em)]δ vs. T where an upturn that becomes prominent with the increase in the concentration of PVPh can be observed. The upturn is not evident for blends where PVPh is the minor phase indicating that the phase separation is not related to the high molecular weight fraction, though the Tg of PVPh is strongly dependent on its molecular weight. This second relaxation seen in the tan[thin space (1/6-em)]δ curves is strongly dependent on frequency and becomes more observable at higher frequencies (as seen in Fig. 12). This is because the chain relaxations of the constituent polymers are similar at low frequencies while the relaxations at high frequencies are different relative to the local environment which helps in capturing the presence of a minor phase. This also shows us that it is easy to capture phase separation at higher frequencies in DMTA for the same reason.


image file: d0cp01814g-f11.tif
Fig. 11 Storage modulus, loss modulus, and loss tangent as determined by DMTA for the PVPh–PMMA blend at 10 Hz as a function of temperature: (▲) pure PMMA; (Δ) 10 wt% PVPh; (●) 30 wt% PVPh; (○) 54.5 wt% PVPh. (Reproduced from ref. 99 with permission from ACS, copyright 1996.)

image file: d0cp01814g-f12.tif
Fig. 12 Dynamic mechanical spectra of a PVPh-PMMA blend containing 30 wt% PVPh: (□) 1 Hz; (●) 10 Hz; (○) 30 Hz. (Reproduced from ref. 99 with permission from ACS, copyright 1996.)

Heino et al.100 studied the effect of different modifications of SEBS copolymers on their ability to compatibilize poly(ethylene terephthalate)/polypropylene (PET/PP) blends. Maleic anhydride (MAH) and glycidyl methacrylate (GMA) were grafted to the middle block of SEBS triblock copolymers. The tan[thin space (1/6-em)]δ vs. T curves show a single maximum representing a single glass transition – indicative of miscibility (compatibilization rather). Further to this, we can see that with the addition of the compatibilizer, there is a shift in the peak maxima in PET rich blends indicating the presence of favorable interactions. In PP rich blends, the peak shifts towards the Tg of PP on addition of functionalized compatibilizers as shown in Fig. 13.


image file: d0cp01814g-f13.tif
Fig. 13 tan[thin space (1/6-em)]δ curves of PET/PP blends for (a) PET-rich and (b) PP-rich compositions. (Reproduced from ref. 100 with permission from Wiley, copyright 1997.)

Cesteros et al.101 studied the miscibility in poly(ethylene oxide)/poly(N-vinyl pyrrolidone) using DMTA and DSC. The loss tangent versus temperature graphs of the blends showed an additional maximum which was not present in neat PEO. This additional maximum is due to the presence of another phase of the material. The blend is considered as a mixture of components up to the molecular level thereby giving two maxima corresponding to each of the components.

7 Selective localization of nanoparticles

7.1 Strategic localization of nanoparticles in polymer blends

Incorporation of nanoparticles in polymers has resulted in the development of polymer systems that have enhanced mechanical, optical, and electrical properties. In polymer blends, the nanoparticles are selectively localized in one of the polymer phases12 or at the interface.102 The localization of nanoparticles in polymer blend systems is mainly governed by thermodynamics, kinetics, and viscosity.9,103,104 In various blends even if thermodynamics is the main determining factor according to the wetting equation other factors come into play. In this work, the wetting equation and how it affects localization will not be discussed since they have been extensively explained by many authors.8,9 The similarity in terms of the structures between the nanoparticle and the polymer also governs localization. Most of the carbonaceous nanoparticles in PMMA/SAN are localized in the SAN phase irrespective of thermodynamics (see Table 1). The localization of the carbonaceous nanoparticles such as MWCNTs in this SAN is mainly governed by the π–π interaction between the MWCNT honey-comb structure and the phenyl ring of poly(styrene-acrylonitrile).105 In some cases, amine-functionalized MWCNT nanoparticles were found to be in the PMMA phase and at the interface for acid functionalized carbon nanotubes in a PMMA/SAN polymer blend system.52 In the case of clay nanoparticles, they were found to be localized at the interface of the PMMA/SAN blend. Grafting of polymer chains on the surface of nanoparticles can alter the localization of the nanoparticles depending on many factors. The strategic location of nanoparticles is of paramount importance in the application of polymer blends. The high electrical conductivity of polymer blends containing conductive nanoparticles can be enhanced when double percolation is achieved. This selective localization of nanoparticles to obtain double percolation can be used in applications such as EMI shielding.106 Strategic localization also helps in improving the flame retardancy properties of polymer blends107 since polymers are highly susceptible to fire. Localization of nanoparticles at the interface has been shown to enhance the electrical properties of polymer blends as observed by Hosseinpour et al.108
Table 1 Localization of different nanoparticles in miscible polymer blends prepared by different processing methods
Blend system Nanoparticle Localization Blending method Ref.
PMMA/SAN Graphene oxide SAN Solution mixing 32
PMMA/SAN Reduced graphene oxide SAN Solution mixing 119
PMMA/SAN MWCNT SAN Solution mixing 66
PMMA/SAN Clay PMMA Solution mixing 120
PMMA/SAN Clay Interface Melt mixing 121
PMMA/SAN Fumed silica PMMA Solution mixing 122
PMMA/SAN Amine-MWCNT and acid-MWCNT PMMA Solution mixing 52
Interface
PLA/PMMA Silica PLA and PMMA Melt mixing 123
PS/PVME Silver PVME Solution mixing 64
PS/PVME MWCNT PVME Solution mixing 55
PαMSAN/PMMA Amine-MWCNT and polyethylene modified MWCNT PαMSAN Melt mixing 124
PCL/SAN Silica SAN and Interface Melt mixing 125


7.2 Effects of chain length and graft density on the localization of nanoparticles

The localization of nanoparticles in polymer blends can be tuned by grafting polymer chains on the surface of different nanoparticles. To drive the nanoparticles from a thermodynamically favorable phase A to an unfavorable phase B, the nanoparticles can be grafted with B polymer chains. Many factors must be considered to tune the localization of nanoparticles and one of them is the chain length of the polymer chains. Usually, an increase in the chain length of the grafted polymers results in successful migration of the nanoparticles from A-phase to B-phase. Chung et al.109 were able to control the localization of silica nanoparticles in PMMA/SAN by varying the chain length of PMMA tethered on the silica surface and holding the grafting density constant. They grafted PMMA polymer chains of (Mn) 1800, 21[thin space (1/6-em)]000, and 160[thin space (1/6-em)]000 g mol−1 and observed that the grafted nanoparticles were first located in the SAN phase, then at the interface and in the dPMMA phase respectively.

Both graft density and chain length play a major role in the localization and in delaying the miscibility of polymer blends. Kar et al.110 varied the graft density of polystyrene which was grafted to gold nanoparticles. Two types of grafting densities were probed: the first polymer grafted nanoparticle had a graft density of 1.7 chains per nm2 (chain length of 30[thin space (1/6-em)]000 g mol−1) and the second one had a graft density of 1.2 chains per nm2 (chain length of 53[thin space (1/6-em)]000 g mol−1). The nanoparticles which had a higher chain length were found to be localized in the PS phase (see Fig. 14). This was mainly attributed to favorable interactions between the matrix and the grafted chains. The polymer grafted gold nanoparticles which had more graft density and lesser chain length were found to be localized in the PVME phase. This was because the radius of gyration of the matrix was greater than the radius of gyration of the grafted chains hence resulting in the expulsion of the nanoparticles from the PS phase.


image file: d0cp01814g-f14.tif
Fig. 14 Cartoon showing the selective localization of polymer grafted nanoparticles after phase separation. (Reproduced from ref. 110 with permission from ACS, copyright 2014.)

Liu et al.111 were able to localize PMMA-g-clay nanoparticles on the interface of PMMA/SAN by miscibility variation. The polymer grafted clay nanoparticles were reported to have a low graft density of 0.04 chains per nm2. Initially, the PGNs (polymer grafted nanosheets) were found to be in the SAN phase, and then after annealing, they migrated to the PMMA/SAN interface. They attributed the localization of the PGNs to the favorable interaction between PMMA grafted chains and the SAN matrix. After annealing the interaction was disrupted resulting in the nanoparticle migrating to the interface.

7.3 Janus nanoparticles – strategic localization at the interface

Precise localization of nanoparticles in bi-phasic polymers is a major concern in designing nano functional materials.112 Another novel method of governing the localization of nanoparticles in biphasic polymer blends is the use of Janus nanoparticles. Janus nanoparticles are materials which are sectionalized into two hemispheres,113 possessing both polymer chains of the two-polymer matrix (see Fig. 15). Janus nanoparticles became popular after the French physicist Pierre-Giles de Gennes popularized them in 1991 in his Noble Prize lecture.114 These uniquely designed nanoparticles strongly adsorb at the interface of two polymers. Their adsorption at the interface is much stronger than other homogeneous nanoparticles and surfactants.115,116 The localization of Janus nanoparticles at the interface of polymer blends has been reported to improve the overall mechanical properties of the blends.117 Instead of trapping the nanoparticles at the interface by kinetics or thermodynamics, Janus nanoparticles can be used.
image file: d0cp01814g-f15.tif
Fig. 15 Schematic representation of the interfacial state of different nanoparticles and the dispersed-phase change for polymer blends in different processes. (Reproduced from ref. 118 with permission from ACS, copyright 2018.)

8 Application of miscible polymer blends

8.1 Conducting blends and EMI shielding

Conducting polymer blends have numerous potential applications provided they maintain a stable microstructure during processing. During processing, thermodynamics usually results in coalescence of the droplets; hence to suppress this coalescence nanoparticles have been used.126 Phase separation can act as a tool to induce electrical conductivity in miscible polymer blend systems containing conducting nanoparticles such as carbon nanotubes127 and thermally reduced graphene sheets.59 CNTs can be widely used as fillers in miscible polymer blend systems to enhance conductivity because of their properties such as high aspect ratio, which results in them forming interconnected networks at low filler loading. Phase separation can be used to strategically localize the CNTs in one of the polymer phases or at the interface resulting in percolation at a less filler loading concentration. In their work, Bose et al.128 used a miscible polymer blend system of PαMSAN/PMMA containing functionalized MWCNT and they were able to observe a significant increase in the conductivity of the system after phase separation. They were able to transform an insulating polymer blend system at room temperature to a conducting polymer blend system in melt state due to phase separation.

Due to the many electronic types of equipment being produced nowadays electromagnetic pollution has now tremendously increased. To shield or protect other equipment and to avoid adverse effects of electromagnetic radiation on human health, it is now of paramount importance to design electromagnetic shielding materials.129,130 Miscible polymer blends can be used as a template in fabricating electromagnetic shielding equipment.131 Polymers tend to have a multiplicity of advantages in comparison to metals because they are cheap, easy to fabricate, cannot be affected by corrosion, lightweight, and they can both reflect and absorb electromagnetic radiation when they are used with different fillers. Thermally induced phase separation of miscible polymer blends can be an effective way of designing polymer blends with transient morphology microstructures.127 During phase separation in polymer blends with nanoparticles, selective localization of the nanoparticles occurs in a single phase. Phase separation can act as an effective tool in organizing the nanoparticles in a single-phase resulting in a perfect material that can be an ideal candidate to shield electromagnetic radiation. Xavier et al.132 were able to use the PS/PVME miscible polymer blend system to design a perfect to design a perfect template which shields through phase separation. After phase separating the PS/PVME miscible blend system, the MWCNT was selectively localized in the PVME phase as confirmed by atomic force microscopy. A blend composition 70/30 (wt/wt) with 1 wt% MWNT resulted in a reflection loss of −24 dB at a frequency of 12 GHz and also showed a −36 dB maximum reflection loss at 8.65 Hz. Li et al.133 developed a stretchable electromagnetic interference shielding material from the poly(3,4-ethylenedioxythiophene):polystyrenesulfonate and waterborne polyurethane (PEDOT:PSS/WPU) miscible polymer blend system. They reported that the polymer blend system is miscible at a wide range of blending compositions. The uniqueness of this polymer blend system was due to its efficiency in shielding EMI radiation and also good stretchability making it suitable in different stretchable electronic system applications. This flexible shielding polymer blend system was found to have a shielding effectiveness of 62 dB with a thickness of 0.15 mm.

8.2 Membrane for gas separation

Polymer blend systems can be used in gas separation and this is of paramount importance in many industrial applications. Polymer blends offer numerous advantages over single polymers because they enhance the overall properties of the polymer system such as mechanical strength and thermal properties just to mention a few. The membranes for gas separation should have good selectivity and also should be permeable for effective and efficient gas separation to occur. Usually, the membranes are mainly categorized into two which are the porous membranes having an even pore size distribution and non-porous membranes in which the molecules are adsorbed on the surface of the membrane and are forced to pass through due to external pressure applied. Gas separation by membranes proves to be an ideal solution over other methods because of their multiple advantages such as low energy requirements, low operating cost, and environmental friendliness. In partially miscible polymer blends, the separation is mainly dependent upon the specific volume and the morphology of the system. Permeability of partially miscible polymer blend systems can be predicted using the equation below:
ln[thin space (1/6-em)]Pb = ϕ1[thin space (1/6-em)]ln[thin space (1/6-em)]P1 + ϕ2[thin space (1/6-em)]ln[thin space (1/6-em)]P2
where Pb, P1, P2 are the permeability coefficients of the blend and ϕ is the volume fraction.134

Pure oxygen can find many uses in different types of applications such as in combustion processes, and nitrogen-rich air can be used in food storage and in creating clean environments for semiconductor fabrication. The PPO/PS miscible polymer blend system has been used in permeation characteristic studies for oxygen and nitrogen.135 Separation of hydrogen gas from a mixture of other gases is of great importance because hydrogen gas can be used as a fuel. Membrane technology has found great use in separating hydrogen gas during fermentation processes. Polysulfone–polyimide (PSf/PI) is a classical example of a miscible polymer blend136 which can be used in H2/CO2 separation because of its simplicity in refining the membrane inner structure. Polysulfone improves to a larger extent the durability of the membrane, and it has both good gas permeability and permselectivity. Polyimide is an engineering polymer that has good mechanical properties and excellent chemical resistance. In their work Hamid et al.137 were able to make PSf/PI membranes and found the blend to have high permeation properties in comparison to neat PSf and PI polymers. Thus, their results prove that polymer blending is of paramount importance in enhancing the separation of H2/CO2 gases. Hosseini et al.138 were able to separate and purify hydrogen by making use of a polymer membrane which was fabricated from 3,3′,4,4′-benzophenone tetracarboxylic dianhydride and diamino-phenylindane (matrimid) and poly[2,2′-(1,3-phenylene)-5,5′-bibenzimidazole] (PBI) which was a miscible polymer system as observed by DSC single glass transition temperature and visual inspection. The miscibility of the polymer system was as a result of specific interactions between the N–H groups of PBI and the C[double bond, length as m-dash]O of matrimid which resulted in hydrogen bonding. The use of polymer blends in gas separation is mainly governed by the resulting morphology after blending and the specific interactions between the two polymers. The incorporation of PBI significantly improved the gas separation of the polymer blend system due to the reduction of the fractional free volume. Selectivity was further improved by the modification of the system.

8.3 Proton exchange fuel cells

Proton exchange fuel cells are a type of fuel cells which are used for transport application and have been developed to replace the alkaline fuel cell technology. Researchers are now mainly focusing on this type of fuel cells because they show great potential in providing clean energy. Great work has been done to develop fuel cells that can conduct protons at a high temperature. Development of these cells which can work at high temperatures is mainly made possible by the use of imidazole, pyrazole, and triazole. These polymers contain heteroaromatic groups which show high conductivity at elevated temperatures. The nitrogen groups present in these polymers act as proton acceptors hence enhancing proton conduction. These fuel cells can be fabricated from miscible polymer blends. In their work, Hazarika et al.139 were able to fabricate various compositions of PEM cells from the miscible polymer blend system of polybenzimidazole and poly(vinyl-1,2,4-triazole) through solution mixing. They revealed the miscibility of the two blends by DSC through a single glass transition temperature; solid NMR and FTIR further confirmed the presence of specific interactions. The interaction between the two polymers was as a result of N–H⋯N interactions. The blending of PVT with PBI was shown to increase proton conductivity (see Fig. 16) and this was due to an increase in conductivity as a result of the presence of both imidazole and triazole rings; the authors further postulated that the porous morphology was another significant factor. The authors in their work also mentioned that blending the two polymers improved the thermomechanical stability of the PEM.
image file: d0cp01814g-f16.tif
Fig. 16 Plot showing the increase in proton conductivity after blending. (Reproduced from ref. 139 with permission from ACS, copyright 2012.)

8.4 Barrier properties

Miscible polymer blends have also been used in barrier applications mainly in the food industry. It is of great importance to inhibit the entrance of oxygen and moisture in packed food because they cause chemical and physical deterioration of the food, by facilitating the growth of microorganisms. Organic electronics such as photovoltaics are now being widely used to generate electricity mainly because it is an environmentally friendly method of generating power and makes use of a renewable power source. The main disadvantage of organic electronics besides their low energy conversion is that they are susceptible to damage due to the presence of water vapor and oxygen in the atmosphere. The stability of the organic photovoltaic is mainly dependent on the stability of the photoactive material. Barrier properties of polymers are also significant in protecting organic electronics from air and moisture. To extend the service life of organic electronics, it is of paramount importance to coat them with a barrier film. Miscible biodegradable polymer blends have been used in barrier applications. Sangroniz et al.15 were able to study the barrier properties of biodegradable polymers (PBAT/PH). They concluded that the water vapor transmission rate and oxygen permeability were reduced due to blending in comparison to the neat polymers. The addition of PH to PBAT reduced the free volume, thereby improving the barrier properties of the blend system. It is of great advantage to use natural polymers in fabricating barrier films, but the main disadvantage of them is that they absorb water and are very brittle which makes them less favorable for such application. The blending of two polymers improves their overall properties. In their work Soliman et al.140 were able to fabricate miscible biodegradable films that showed enhanced water barrier properties. The extent of the interaction of two miscible polymers, method of preparation, and whether the blend is in its miscible or immiscible state can affect the barrier properties of the blend system. In their work, Chiou et al.141 studied the gas permeation in PMMA/SAN, a miscible polymer blend system. They took SAN with an AN content of 13.5 and 28 wt% and compared the two. They concluded that the SAN which had 28 wt% showed better barrier properties than the one with 13.5 wt%. They postulated that this was because polyacrylonitrile has better gas barrier properties than polystyrene. They went a step further and compared the permeability of the blend system before and after phase separation and came to understand that phase-separated polymer blends showed the same permeability as miscible polymer blends. Finally, they compared the method of preparation of the PMMA/SAN membrane. The membranes which were prepared by the melt mixing method showed similar results to the ones prepared by solution mixing except for argon, nitrogen, and methane gas which showed low permeability in melt mixed membranes. They attributed this difference to the molecular orientation of the films during extrusion.

PC/PMMA is another polymer blend that can be used in barrier property application. The miscibility of PC/PMMA is mainly governed by the molecular weight of each component. There has been a wide debate on the miscibility of PC/PMMA but it has been proved that there are specific interactions that exist between the ester group of PMMA and the phenyl ring of PC leading to n–π complex formations.142 In their work, Kim et al.143 were able to study the barrier properties of PC/PMMA in its miscible and immiscible state. The phase-separated membranes were classified into co-continuous and droplet matrix morphology. The droplet matrix morphology showed higher diffusion of both nitrogen and oxygen gas followed by the co-continuous morphology and finally the miscible membrane.

8.5 Membranes for lithium-ion battery application

Another classical example of miscible polymer blends that can be used in fuel cell applications is PBI/PSF. Polybenzimidazole and polysulfone are immiscible polymer blends, but they can be fine-tuned to become miscible by incorporating sulfonate functional groups in PSF so as to allow interaction with PBI. These miscible polymer blends can be used in polymeric membranes as electrolytes in fuel cells.144

8.6 Biomedical and drug delivery

Biological molecules have been greatly used in drug delivery and tissue engineering applications. Irrespective of the fact that many of the biological molecules are non-toxic, biocompatible, and biodegradable, they also have numerous shortfalls such as poor mechanical properties, poor cell attachment, and weak processability. To counteract the shortfalls of these polymers, blending comes into play because it improves the overall properties of the system. In their work Ghaffari-Bohlouli et al.145 blended PLDLLA (poly(L-lactide-co-D,L-lactide)) with PAA (polyacrylic acid) through solution mixing. They reported that by adding PAA to PLDLLA, there was an improvement in the hydrophilicity and the degradability of the blend system. Although there was a decrease in the tensile strength and the Young's modulus there was an improvement in the tensile stress. They also reported improved cell viability of the system which makes it a perfect candidate in tissue engineering applications.

Miscible polymer blends can also find very important use in drug delivery applications.146 Karavas et al.147 were able to use PVP/HPMC for drug delivery applications. They reported that PVP/HPMC was miscible in all compositions as determined by DSC. The miscibility of the blend was because of the specific interactions between the carbonyl group of PVP and the hydroxyl group of HPMC. This polymer blend system which they used, showed enhanced mucoadhesive properties which predicted the pulsatile formulations of FELO, an active pharmaceutical ingredient in the two-layered tablets.

8.7 Corrosion protection

Stainless steel is of great importance in many industrial applications because of its outstanding mechanical properties and relatively low cost. The only issue which hinders stainless steel to be used in aggressive media is its susceptibility to corrosion. PVDF/PMMA miscible polymer blends have been reported to be used in corrosion protection of metals.148 PVDF alone can be used in coating applications because of its excellent outdoor properties, good wear resistance, and good flexibility. Blending PVDF with PMMA has been considered to be more effective in improving crack resistance and adhesion properties. The two polymers are miscible by melt blending them at high temperatures; when the coating film cools, the formation of the crystallization phase is initiated, and the crystallized PVDF coexists with the amorphous portion of PMMA.

8.8 Light-emitting diodes

Polymer blends have also found use in the fabrication of light-emitting diodes. Usually, the basic requirements of a light-emitting diode material are that it must be transparent to allow transmittance of light and should have a high working temperature. Polycarbonate is one of the polymer materials which is being used to make LEDs, because of its high mechanical properties and transparent nature. Of late, PLA/PMMA, a miscible polymer blend, has been found to be a better material in the fabrication of LEDs.123 PLA is a biodegradable polymer, hence it improves the environmental friendliness of the overall blend system (Table 2).
Table 2 A summary of the different miscible polymer blend systems and their applications
Polymer blend system Application
PαMSAN/PMMA Conducting polymer material for EMI shielding
PS/PVME EMI shielding
PPO/PS Gas separation
PSf/PI Gas separation
PVT/PBI Proton exchange fuel cells
PBAT/PH Moisture and gas barrier application
PMMA/SAN Moisture and gas barrier application
PC/PMMA Moisture and gas barrier application
PVDF/PMMA Membranes for lithium-ion battery
PBI/PSF Membranes for lithium-ion battery
PVP/HPMC Drug delivery
PLDLLA/PAA Tissue engineering
PLA/PVAc Shape memory polymers for drug delivery
PVDF/PMMA Corrosion protection
PLA/PMMA Light-emitting diodes


8.9 Shape memory polymers

Shape memory polymers are of great importance due to their wide biomedical applications. These smart materials when exposed to a certain stimulus such as pH, magnetic field, heat, or electric field can change from their temporary shape to original shape. It is of paramount importance to design SMPs which have excellent mechanical properties without compromising their shape memory behavior. The easiest way to enhance the mechanical property of a polymer which exhibits shape memory behavior is by blending. The blending of two polymers usually results in an immiscible polymer blend system, due to the factors which have been described earlier in the review; hence it is essential to make polymer blends which are miscible since this can enhance the mechanical properties of the system. In their work Sabzi et al.149 were able to blend poly(lactic acid) with poly(vinyl acetate) in the presence of graphene to fabricate a triple-shape memory system. Their choice of polymer was because PLA shows good shape memory behavior which can be further improved by the addition of graphene nanoplatelets. When blended with PVAc, PLA enhanced the toughness without compromising the shape memory behavior. Zhang et al.150 in their work were able to increase the toughness of PLA by blending with a polyamide elastomer to create a miscible polymer blend system. They postulated that using PLA alone for shape memory application won’t suffice due to its brittleness and low toughness, so to increase its toughness it had to be blended with PAE. With only 10 wt% of PAE, they were able to achieve a significant increase in elongation whilst retaining the shape memory properties of the polymer blend system.

9 Conclusion

The main purpose of this review was to expatiate the fundamental principles governing miscibility in polymer blend systems in the presence of different nanoparticles and how the polymer blends can be used in different applications. The review highlights on

• The processing methods used in fabricating miscible polymer blends which are melt mixing and solution mixing methods. The choice of the ideal processing method depends on the extent of the miscibility of the system. Different processing methods affect the final properties of the fabricated polymer blend systems.

• Enthalpy and entropy are the most elaborated factors governing miscibility, but this review went a step further in explaining other factors such as the copolymer repulsion effect mainly evident in the PMMA/SAN polymer blend system. Usually, the contributing factor which results in negative enthalpy is the attractive interactions but in the case of PMMA/SAN, it is quite different.

• Different nanoparticles have been seen to enhance the phase separation diagram and interestingly polymer grafted nanoparticles are more effective in increasing the miscibility of polymer blends, which can be clearly explained by statistical mechanics.

• Different types of methods used to probe the phase separation temperature of a miscible polymer blend system have been explained including the advantages and disadvantages associated with each method.

• The aspect of selective localization of nanoparticles in one of the phases of the polymer blend system has been explained in detail mainly focusing on the effect of chain length and graft density of polymer grafted nanoparticles, Janus nanoparticles, and π–π interactions between carbonaceous nanoparticles and phenyl ring containing polymers such as SAN.

• Lastly, the applications of miscible polymer blend systems in the biomedical field, membranes for gas separation, barrier materials, fabrication of lithium batteries, and corrosion application just to mention a few have been explored.

Conflicts of interest

There are no conflicts to be declared.

Acknowledgements

T. S. M. would like to acknowledge the Office of International Relations, Indian Institute of Science, for the PhD research scholarship.

References

  1. K. B. Kancherla, D. B. Subbappa, S. R. Hiremath, B. Raju and D. R. Mahapatra, Composites, Part A, 2019, 118, 131–141 CrossRef CAS.
  2. Z. Sheng, G. Jia, S. Yongyuan, L. Zhaoxia, J. Xiaodong, L. Xiaodong, G. Xiaoyu, L. Hongfei and S. Jun, Polym. Compos., 2018, 40, E1884–E1892 CrossRef.
  3. G. P. Kar, S. Biswas and S. Bose, Phys. Chem. Chem. Phys., 2015, 17, 14856–14865 RSC.
  4. J. Colmenero and A. Arbe, Soft Matter, 2007, 3, 1474–1485 RSC.
  5. G. P. Kar, A. Bharati, P. Xavier, G. Madras and S. Bose, Phys. Chem. Chem. Phys., 2015, 17, 868–877 RSC.
  6. H. Chao and R. A. Riggleman, Polymer, 2013, 54, 5222–5229 CrossRef CAS.
  7. C. R. Bilchak, Y. Huang, B. C. Benicewicz, C. J. Durning and S. K. Kumar, ACS Macro Lett., 2019, 8, 294–298 CrossRef CAS.
  8. F. Fenouillot, P. Cassagnau and J. Majeste, Polymer, 2009, 50, 1333–1350 CrossRef CAS.
  9. S. P. Pawar and S. Bose, Phys. Chem. Chem. Phys., 2015, 17, 14470–14478 RSC.
  10. M. Sharma, G. Madras and S. Bose, Macromolecules, 2015, 48, 2740–2750 CrossRef CAS.
  11. S. M. N. Sultana, S. P. Pawar and U. Sundararaj, Ind. Eng. Chem. Res., 2019, 58, 11576–11584 CrossRef CAS.
  12. M. Cao, M. Sun, Z. Zhang, R. Xia, P. Chen, B. Wu, J. Miao, B. Yang and J. Qian, Polym. Test., 2019, 78, 1–7 CrossRef.
  13. P. Bhawal, S. Ganguly, T. K. Das, S. Mondal and L. Nayak, Mater. Sci. Eng., 2019, 245, 95–106 CrossRef CAS.
  14. F. Faraguna and P. Petra, Polymer, 2017, 132, 325–341 CrossRef CAS.
  15. A. Sangroniz, L. Sangroniz, A. Gonzalez, A. Santamaria, J. del Rio, M. Iriarte and A. Etxeberria, Eur. Polym. J., 2019, 115, 76–85 CrossRef CAS.
  16. A. Etxeberria, S. Guezala, J. J. Iruin, J. G. De La Campa and J. De Abajo, J. Appl. Polym. Sci., 1997, 68, 2141–2149 CrossRef.
  17. K. Ke, Y. Wang, X. Q. Liu, J. Cao, Y. Luo, W. Yang, B. H. Xie and M. B. Yang, Composites, Part B, 2012, 43, 1425–1432 CrossRef CAS.
  18. G. Sui, D. Liu, Y. Liu, W. Ji, Q. Zhang and Q. Fu, Polymer, 2019, 182, 121838 CrossRef.
  19. E. H. Backes, D. N. Pires, L. C. Costa, F. R. Passador and L. A. Pessan, J. Compos. Sci., 2019, 3, 52 CrossRef CAS.
  20. D. Ku, J. Jaśkowska and R. Jasiński, J. Heterocycl. Chem., 2019, 56, 1498–1504 CrossRef.
  21. A. Shah and M. Gupta, Antec-Conference Proceedings, 2004, 443–447.
  22. K. Chaudhuri, S. Poddar, H. Pol, A. Lele, A. Mathur, G. S. Srinivasa Rao and R. Jasra, Polym. Eng. Sci., 2018, 59, 821–829 CrossRef.
  23. H. Tanaka, Phys. Rev. Lett., 1996, 76, 787–790 CrossRef CAS.
  24. M. Sharma, K. Sharma and S. Bose, J. Phys. Chem. B, 2013, 117, 8589–8602 CrossRef CAS.
  25. H. Feng, C. Ye and Z. Feng, Polym. J., 2014, 28, 661–664 CrossRef.
  26. B. Lu, K. Lamnawar, A. Maazouz and H. Zhang, Soft Matter, 2016, 12, 3252–3264 RSC.
  27. W. Liu, Y. Pang, M. Wu, K. Qin and W. Zheng, Polymer, 2019, 166, 63–71 CrossRef CAS.
  28. W. Chang, C. Wang and C. Chen, Electrochim. Acta, 2019, 296, 268–275 CrossRef CAS.
  29. H. Keskkula and D. R. Paul, J. Appl. Polym. Sci., 1986, 31, 1189–1197 CrossRef CAS.
  30. M. E. Fowler, J. W. Barlow and D. R. Paul, Polymer, 1987, 28, 1177–1184 CrossRef CAS.
  31. P. Xavier and S. Bose, J. Phys. Chem. B, 2013, 117, 8633–8646 CrossRef CAS.
  32. T. S. Muzata, G.P. Kar Jagadeshvaran and S. Bose, Phys. Chem. Chem. Phys., 2018, 20, 19470–19485 RSC.
  33. P. Xavier, K. Sharma, K. Elayaraja, K. S. Vasu, A. K. Sood and S. Bose, RSC Adv., 2014, 4, 12376–12387 RSC.
  34. Y. Huang, S. Jiang, G. Li and D. Chen, Acta Mater., 2005, 53, 5117–5124 CrossRef CAS.
  35. Y. Kou, X. Cheng and C. W. Macosko, Macromolecules, 2019, 52, 7625–7637 CrossRef CAS.
  36. V. V. Ginzburg, Macromolecules, 2005, 38, 2362–2367 CrossRef CAS.
  37. G. P. Kar, P. Xavier and S. Bose, Phys. Chem. Chem. Phys., 2014, 16, 17811–17821 RSC.
  38. G. P. Kar, A. Bharati, P. Xavier, G. Madras and S. Bose, Phys. Chem. Chem. Phys., 2015, 17, 868–877 RSC.
  39. J. Pribyl, B. Benicewicz, M. Bell, K. Wagener, X. Ning, L. Schadler, A. Jimenez and S. Kumar, ACS Macro Lett., 2019, 8, 228–232 CrossRef CAS.
  40. C. R. Bilchak, E. Buenning, M. Asai, K. Zhang, C. J. Durning, S. K. Kumar, Y. Huang, B. C. Benicewicz, D. W. Gidley, S. Cheng, A. P. Sokolov, M. Minelli and F. Doghieri, Macromolecules, 2017, 50, 7111–7120 CrossRef CAS.
  41. K. Kim, M. Soo, Y. Na, J. Choi, S. A. Jenekhe and F. Sunjoo, Org. Electron., 2019, 65, 305–310 CrossRef CAS.
  42. W. U. Huynh, J. J. Dittmer and A. P. Alivisatos, Science, 2002, 295, 2425–2427 CrossRef CAS.
  43. F. B. Barlas, E. Aydindogan, M. Arslan, S. U. N. A. Timur and Y. Yagci, J. Appl. Polym. Sci., 2019, 136, 47250 CrossRef.
  44. M. Asai, D. Zhao and S. K. Kumar, ACS Nano, 2017, 11, 7028–7035 CrossRef CAS.
  45. T. Hao, Y. Ming, S. Zhang, D. Xu and R. Liu, Mol. Simul., 2019, 46, 678–688 CrossRef.
  46. M. J. A. Hore, Soft Matter, 2019, 15, 1120–1134 RSC.
  47. D. Sunday, J. Ilavsky and D. L. Green, Macromolecules, 2012, 45, 4007–4011 CrossRef CAS.
  48. D. L. Green and J. Mewis, Langmuir, 2006, 22, 9546–9553 CrossRef CAS.
  49. S. K. Kumar, N. Jouault, B. Benicewicz and T. Neely, Macromolecules, 2013, 46, 3199–3214 CrossRef CAS.
  50. M. Pakravan, M. Heuzey and A. Ajji, Macromolecules, 2012, 45, 7621–7633 CrossRef CAS.
  51. A. Gharachorlou and F. Goharpey, Macromolecules, 2008, 41, 3276–3283 CrossRef CAS.
  52. K. Sharma, M. Sharma, A. Chandra and S. Bose, Macromol. Chem. Phys., 2013, 214, 2651–2669 CrossRef CAS.
  53. Y. Niu and Z. G. Wang, Macromolecules, 2006, 39, 4175–4183 CrossRef CAS.
  54. J. K. Yeganeh, F. Goharpey and R. Foudazi, RSC Adv., 2012, 2, 8116 RSC.
  55. P. Xavier, K. M. Nair, K. Lasitha and S. Bose, Phys. Chem. Chem. Phys., 2016, 18, 29226–29238 RSC.
  56. X. Hao, J. Kaschta, Y. Pan, X. Liu and D. W. Schubert, Polymer, 2016, 82, 57–65 CrossRef CAS.
  57. J. K. Yeganeh, F. Goharpey, E. Moghimi, G. Petekidis and R. Foudazi, Soft Matter, 2014, 10, 9270–9280 RSC.
  58. J. Sharma and N. Clarke, J. Phys. Chem. B, 2004, 108, 13220–13230 CrossRef CAS.
  59. G. Vleminckx, S. Bose, J. Leys, J. Vermant, M. Wübbenhorst, A. A. Abdala, C. Macosko and P. Moldenaers, ACS Appl. Mater. Interfaces, 2011, 3, 3172–3180 CrossRef CAS.
  60. P. Xavier and S. Bose, Phys. Chem. Chem. Phys., 2015, 17, 14972–14985 RSC.
  61. M. Kapnistos, A. Hinrichs, D. Vlassopoulos, S. H. Anastasiadis, A. Stammer and B. A. Wolf, Macromolecules, 1996, 9297, 7155–7163 CrossRef.
  62. W. Yu, R. Li and C. Zhou, Polymer, 2011, 52, 2693–2700 CrossRef CAS.
  63. D. Schwahn, V. Pipich and D. Richter, Macromolecules, 2012, 45, 2035–2049 CrossRef CAS.
  64. P. Xavier, A. Bharati, G. Madras and S. Bose, Phys. Chem. Chem. Phys., 2014, 16, 21300–21309 RSC.
  65. A. Ajji and L. Choplin, Macromolecules, 1991, 24, 5221–5223 CrossRef CAS.
  66. H. Li, M. Zuo, T. Liu, Q. Chen, J. Zhang and Q. Zheng, RSC Adv., 2016, 6, 10099–10113 RSC.
  67. M. Zuo and Q. Zheng, Macromol. Chem. Phys., 2006, 207, 1927–1937 CrossRef CAS.
  68. C. D. Chuang, C. D. Han and H. K. Chuang, J. Appl. Polym. Sci., 1985, 30, 4431–4454 CrossRef.
  69. A. R. Nesarikar, Macromolecules, 1995, 28, 7202–7207 CrossRef CAS.
  70. N. Nyamweya and S. W. Hoag, Pharm. Res., 2000, 17, 625–631 CrossRef CAS.
  71. J. M. G. Cowie, S. Harris, J. L. Gomez Ribelles, J. M. Meseguer, F. Romero and C. Torregrosa, Macromolecules, 1999, 32, 4430–4438 CrossRef CAS.
  72. S. F. Lau, J. Pathak and B. Wunderlich, Macromolecules, 1982, 15, 1278–1283 CrossRef CAS.
  73. C. Pellerin, I. Pelletier, M. Pezolet and R. E. Prud’Homme, Macromolecules, 2003, 36, 153–161 CrossRef CAS.
  74. M. Aubin and R. E. Prud’Homme, Macromolecules, 1988, 21, 2945–2949 CrossRef CAS.
  75. C. Lau and Y. Mi, J. Polym. Sci., Part B: Polym. Phys., 2001, 39, 2390–2396 CrossRef CAS.
  76. B. Min, X. Qiu, M. D. Ediger, M. Pitsikalis and N. Hadjichristidis, Macromolecules, 2001, 34, 4466–4475 CrossRef CAS.
  77. E. G. Crispim, A. F. Rubira and E. C. Muniz, Polymer, 1999, 40, 5129–5135 CrossRef CAS.
  78. J. R. Fried, F. E. Karasz and W. J. MacKnight, Macromolecules, 1978, 11, 150–158 CrossRef CAS.
  79. H. B. Ravikumar, C. Ranganathaiah, G. N. Kumaraswamy and S. Thomas, Polymer, 2005, 46, 2372–2380 CrossRef CAS.
  80. C. D. Han, Polymer blends and composites in multiphase systems, American Chemical Society, 1984 Search PubMed.
  81. J. W. Schurer, A. de Boer and G. Challa, Polymer, 1975, 16, 201–204 CrossRef CAS.
  82. L. J. Hughes and G. L. Brown, J. Appl. Polym. Sci., 1961, 5, 580–588 CrossRef CAS.
  83. L. A. Utracki and C. A. Wilkie, Polymer blends handbook, Kluwer academic publishers, Dordrecht, 2002, vol. 1, 2 Search PubMed.
  84. F. Alvarez, A. Alegría and J. Colmenero, Macromolecules, 1997, 30, 597–604 CrossRef CAS.
  85. A. Alegria, J. Colmenero, K. L. Ngai and C. M. Roland, Macromolecules, 1994, 27, 4486–4492 CrossRef CAS.
  86. O. Urakawa, Y. Fuse, H. Hori, Q. Tran-Gong and O. A. Yano, Polymer, 2001, 42, 765–773 CrossRef CAS.
  87. M. Sharma, G. Madras and S. Bose, Macromolecules, 2014, 47, 1392–1402 CrossRef CAS.
  88. R. E. Wetton, W. J. MacKnight, J. R. Fried and F. E. Karasz, Macromolecules, 1978, 11, 158–165 CrossRef CAS.
  89. C. M. Roland and K. L. Ngai, Application of Scattering Methods to the Dynamics of Polymer Systems, 1993, pp. 75–79 Search PubMed.
  90. A. Zetsche and E. W. Fischer, Acta Polym., 1994, 45, 168–175 CrossRef CAS.
  91. A. Jonas, R. Legras and J. P. Issi, Polymer, 1991, 32, 3364–3370 CrossRef CAS.
  92. K. L. Ngai and R. W. Rendell, J. Non-Cryst. Solids, 1991, 131, 942–948 CrossRef.
  93. K. L. Ngai, R. W. Rendell, A. K. Rajagopal and S. Teitler, Ann. N. Y. Acad. Sci., 1986, 484, 150–184 CrossRef CAS.
  94. D. J. Plazek and K. L. Ngai, Macromolecules, 1991, 24, 1222–1224 CrossRef CAS.
  95. C. M. Roland and K. L. Ngai, Macromolecules, 1991, 24, 2261–2265 CrossRef CAS.
  96. J. A. Campbell, A. A. Goodwin and G. P. Simon, Polymer, 2001, 42, 4731–4741 CrossRef CAS.
  97. S. Havriliak and S. A. Negami, Polymer, 1967, 8, 161–210 CrossRef CAS.
  98. R. E. Wetton and P. J. Corish, Polym. Test., 1988, 8, 303–312 CrossRef CAS.
  99. D. Li and J. Brisson, Macromolecules, 1996, 29, 868–874 CrossRef CAS.
  100. M. Heino, J. Kirjava, P. Hietaoja and J. A. seppälä, J. Appl. Polym. Sci., 1997, 65, 241–249 CrossRef CAS.
  101. L. C. Cesteros, J. R. Quintana, J. A. Fernández and I. A. Katime, J. Polym. Sci., Part B: Polym. Phys., 1989, 27, 2567–2576 CrossRef CAS.
  102. Z. Zhang, M. Cao, P. Chen, B. Yang, B. Wu, J. Miao, R. Xia and J. Qian, Mater. Des., 2019, 177, 1–10 Search PubMed.
  103. C. Qu, H. Yang, D. Liang, W. Cao and Q. Fu, J. Appl. Polym. Sci., 2006, 104, 2288–2296 CrossRef.
  104. R. Salehiyan, M. Nofar, S. S. Ray and V. V. Ojijo, J. Phys. Chem. C, 2019, 123, 19195–19207 CrossRef CAS.
  105. G. Scalia, J. P. Lagerwall, M. Haluska, U. Dettlaff-Weglikowska, F. Giesselmann and S. Roth, Phys. Status Solidi B, 2006, 243, 3238–3241 CrossRef CAS.
  106. R. Ravindren, S. Mondal, P. Bhawal, S. Mahammad and N. Ali, Polym. Compos., 2019, 40, 1404–1418 CrossRef CAS.
  107. J. P. Cao, X. Zhao, J. Zhao, J. Zha, G. Hu and Z. Dang, ACS Appl. Mater. Interfaces, 2013, 5, 6915–6924 CrossRef CAS.
  108. A. Hosseinpour, R. Nasseri, S. Ghiassinejad, M. Mehranpour and A. A. Katbab, Polym. Eng. Sci., 2019, 59, 447–456 CrossRef CAS.
  109. H. Chung, J. Kim, K. Ohno and R. J. Composto, ACS Macro Lett., 2012, 1, 252–256 CrossRef CAS.
  110. G. P. Kar, N. Begam, J. K. Basu and S. Bose, Macromolecules, 2014, 47, 7525–7532 CrossRef CAS.
  111. T. Liu, H. Zhang, M. Zuo, W. Zhang, W. Zhu and Q. Zheng, Compos. Sci. Technol., 2019, 169, 110–119 CrossRef CAS.
  112. B. Sarkar and P. Alexandridis, Prog. Polym. Sci., 2015, 40, 33–62 CrossRef CAS.
  113. F. Liang, K. Shen, X. Qu, C. Zhang, Q. Wang, J. Li, J. Liu and Z. Wang, Angew. Chem., Int. Ed., 2011, 123, 2427–2430 CrossRef.
  114. P. G. de Gennes, Soft matter (Nobel lecture), Angew. Chem., Int. Ed. Engl., 1992, 31, 842–845 CrossRef.
  115. B. P. Binks and P. D. I. Fletcher, Langmuir, 2001, 17, 4708–4710 CrossRef CAS.
  116. Y. Nonomura, S. Komura and K. Tsujii, Langmuir, 2004, 20, 11821–11823 CrossRef CAS.
  117. Y. Hou, G. Zhang, X. Tang, Y. Si, X. Song, F. Liang and Z. Yang, Macromolecules, 2019, 52, 3863–3868 CrossRef CAS.
  118. W. You and W. Yu, Langmuir, 2018, 34, 11092–11100 CrossRef CAS.
  119. C. Y. Lin, M. Zuo, H. H. Li, T. Liu and Q. Zheng, Chin. J. Polym. Sci., 2015, 33, 1162–1175 CrossRef CAS.
  120. D. Z. Pang, M. Zuo, J. S. Zhao and Q. Zheng, Chin. J. Polym. Sci., 2013, 31, 1470–1483 CrossRef CAS.
  121. M. H. Lee, C. H. Dan, J. H. Kim, J. Cha, S. Kim, Y. Hwang and C. H. Lee, Polymer, 2006, 47, 4359–4369 CrossRef CAS.
  122. M. Du, Q. Wu, M. Zuo and Q. Zheng, Eur. Polym. J., 2013, 49, 2721–2729 CrossRef CAS.
  123. J. H. Wu, M. C. Kuo and C. W. Chen, J. Appl. Polym. Sci., 2015, 32, 32 Search PubMed.
  124. S. Bose, R. Cardinaels, C. Özdilek, J. Leys, J. W. Seo, M. Wübbenhorst and P. Moldenaers, Eur. Polym. J., 2014, 53, 253–269 CrossRef CAS.
  125. A. A. Naziri, M. Ehsani, H. A. Khonakdar, F. Hemmati and S. H. Jafari, J. Appl. Polym. Sci., 2020, 137, 48679 CrossRef CAS.
  126. S. Vandebril, J. Vermant and P. Moldenaers, Soft Matter, 2010, 6, 3353–3362 RSC.
  127. M. Lee, H. Jeon, B. H. Min and J. H. Kim, J. Appl. Polym. Sci., 2011, 121, 743–749 CrossRef CAS.
  128. S. Bose, C. Ozdilek, J. Leys, J. W. Seo, M. Wubbenhorst, J. Vermant and P. Moldenaers, ACS Appl. Mater. Interfaces, 2010, 2, 800–807 CrossRef CAS.
  129. Y. Bhattacharjee, V. Bhingardive, S. Biswas and S. Bose, RSC Adv., 2016, 6, 112614–112619 RSC.
  130. M. Sharma, D. Singh, A. Menon, G. Madras and S. Bose, ChemistrySelect, 2018, 3, 1189–1201 CrossRef CAS.
  131. S. Bose, M. Sharma, A. Bharati, P. Moldenaers and R. Cardinaels, RSC Adv., 2016, 6, 26959–26966 RSC.
  132. P. Xavier and S. Bose, RSC Adv., 2014, 4, 55341–55348 RSC.
  133. P. Li, D. Du, L. Guo, Y. Guo and J. Ouyang, J. Mater. Chem. C, 2016, 4, 6525–6532 RSC.
  134. H. A. Mannan, H. Mukhtar, T. Murugesan, R. Nasir, D. F. Mohshim and A. Mushtaq, Chem. Eng. Technol., 2013, 36, 1838–1846 CrossRef CAS.
  135. S. Hyum, D. Kim and D. Sung, J. Membr. Sci., 1997, 127, 9–15 CrossRef.
  136. G. C. Kapantaidakis, S. P. Kaldis, X. S. Dabou and G. P. Sakellaropoulos, J. Membr. Sci., 1996, 110, 239–247 CrossRef CAS.
  137. M. A. A. Hamid, Y. T. Chung, R. Rohani and M. U. M. Junaidi, Sep. Purif. Technol., 2019, 209, 598–607 CrossRef.
  138. S. S. Hosseini, M. M. Teoh and T. S. Chung, Polymer, 2008, 49, 1594–1603 CrossRef CAS.
  139. M. Hazarika and T. Jana, ACS Appl. Mater. Interfaces, 2012, 4, 5256–5265 CrossRef CAS.
  140. E. A. Soliman and M. Furuta, Food Nutr. Sci., 2014, 1040–1055 Search PubMed.
  141. J. S. Chiou and D. R. Paul, J. Appl. Polym. Sci., 1987, 34, 1037–1056 CrossRef CAS.
  142. A. Asano, K. Takegoshi and K. Hikichi, Polym. J., 1992, 24, 473–477 CrossRef CAS.
  143. M. H. Kim, J. H. Kim, C. K. Kim, Y. S. Kang, H. C. Park and J. O. Won, J. Polym. Sci., Part B: Polym. Phys., 1999, 37, 2950–2959 CrossRef CAS.
  144. V. Deimede, G. A. Voyiatzis, J. K. Kallitsis, L. Qingfeng and N. J. Bjerrum, Macromolecules, 2000, 33, 7609–7617 CrossRef CAS.
  145. P. Ghaffari-Bohlouli, M. Shahrousvand, P. Zahedi and M. Shahrousvand, Int. J. Biol. Macromol., 2019, 122, 1008–1016 CrossRef CAS.
  146. S. E. Ibim, A. M. Ambrosio, M. S. Kwon, S. F. El-Amin, H. R. Allcock and C. T. Laurencin, Biomaterials, 1997, 18, 1565–1569 CrossRef CAS.
  147. E. Karavas, E. Georgarakis and D. Bikiaris, Eur. J. Pharm. Biopharm., 2006, 64, 115–126 CrossRef CAS.
  148. E. Husain, A. A. Nazeer, J. Alsarraf, M. Murad and A. Shekeban, J. Coat. Technol. Res., 2018, 15, 945–955 CrossRef CAS.
  149. M. Sabzi, M. Babaahmadi and M. Rahnama, ACS Appl. Mater. Interfaces, 2017, 9, 24061–24070 CrossRef CAS.
  150. W. Zhang, L. Chen and Y. Zhang, Polymer, 2009, 50, 1311–1315 CrossRef CAS.

This journal is © the Owner Societies 2020